Tag Archives: RIMS

Integrating DSpace #or2017

Abstracts

Harvesting a Rich Crop: Research Publications and Cultural Collections in DSpace by Andrew Veal, Jane Miller

Currently DSpace v3.2, Repository Tools 1.7.1; upgrading to DSpace v5.6, RT 1.7.4

Wanted independent identity for each major collection area especially research publications and cultural collections; and to avoid weirdly mixed search results – so decided on a multi-tenancy approach. Four repositories on four domains. So could make customisations appropriate to specific collections.

  • research publications (via Elements and self-deposit for theses)
  • cultural collections (digitised; populated by OAI from archives collection and by bulk ingests via csv)
    • 77,000 records: pdf, images, architectural drawings, complete books, audio, video which requires specific display options. Collections based on ownership/subject. Files stored in external archive with metadata stored in DSpace and linking back to file; thumbnail generated on the file.
    • AusStage pilot project – relational index (contributors, productions) linked with digital assets (reviews, photos, video). So eg an event record has a “digital assets” link which brings back a search based on an id shared by related records.
    • Created custom “melbourne.sorting.key” field to enable different sort orders eg for maps where date of accession is irrelevant.
  • coursework resources (eg past exams; architectural drawings for a specific course) – no sitemap or OAI feed
  • admin collections (for ERA)

Couldn’t have done it without service provider (Atmire). Have done lots of business analysis to say what they want, for Atmire to set up. Downside of success is now stakeholders thinks it’s easy to fix anything!

Future:

  • develop gallery/lightbox interface
  • upgrade to 5.6; improve Google Scholar exposure
  • OAI harvesting of additional cultural collections
  • look at thesis preservation via Archivematica

DSpace in the centre by Peter Matthew Sutton-Long

Acknowledges Dr Agustina Martinez-Garcia who did much of the integrations work

[Follows up a bit on Arthur Smith’s presentation earlier so I won’t repeat too much background from there.] Before integration, had separate systems for OA publication and research dataset submissions, e-thesis submissions, Apollo repository, CRIS system for REF. This meant a lot of copy-pasting for admins from the manual submission form into repository submission for. And researchers had to enter data in CRIS (Elements) as well as submitting for repository! Also hard to report on eg author collaborations.

Approved June 2016 to integrate things to meet OA requirements, monitor compliance, help researchers share data, allow electronic deposit of theses, integrate systems with community-drive standards for the dissemination of research activities data.

Item deposited in Elements to repository via repository tools connector (though not all files are passed through). An e-theses system feeds into the repository too. Zendesk is also integrated – any deposit creates a Zendesk ticket, which can be used for communication with researchers.

Researchers can work with a single system. They can add grants and links to publications, link to their ORCID profiles (though they don’t seem to want to), obtain DOIs for every dataset and publication (so some people submit old data just to get this DOI; or submit data early, or submit a placeholder to get a DOI they can cite in their article).

Fewer systems for team to access and manage, enhanced internal workflows.

In future want to integrate VIVO.

DSpace for Cultural Heritage: adding support for images visualization,audio/video streaming and enhancing the data model by Andrea Bollini, Claudio Cortese, Giuseppe Digilio, Riccardo Fazio, Emilia Groppo, Susanna Mornati, Luigi Andrea Pascarelli, Matteo Perelli

DSpace-GLAM built by 4Science as an extension to DSpace, which started from discussions around challenges faced by digital humanities. Have to deal with different typologies, formats, structures, scales – and that’s only the first level of complexity. In addition, most data are created/collected by people (not instruments) so affected by personality, place, time, and may be fragmentary, biased. Has to be analysed with contextual information.

How to do this in a digital library management system? Need tools for:

  • modelling, visualising, analysing – quantitatively and qualitatively, and collaboratively
  • highlighting relationships between data
  • explaining interpretations
  • entering the workflow/network scholars are working in

DSpace-GLAM built on top of DSpace and DSpace-CRIS.

  • Flexible/extensible data model – persons, families, events, places, concepts. When you create a “creator-of” relationship, it automatically creates the inverse “created-by” relationship. Can be extended to work with special metadata standards. By setting these up you can see relationships between people, events, etc.
  • with various add-ons
    • IIIF compliant image viewer addon with presentation API, image API, search API, authentication API coming soon. Gives a “See online” option (instead of just downloading) which shows the image, or PDF, or… in an integrated Universal Viewer player: a smooth interaction with the image, alongside metadata about the object, and linking with the OCR/transcription (including right-to-left writing systems). Sharing and reusing with proper attribution.
    • Audio/video streaming with open source stack: transcoding, adaptive streaming, mpeg-dash standard. DASH standard protocol lets you share video along with access to server to provide zoom to make sure the content stays in the digital library so complete access to stats and ensure people see ownership.
    • Visualising and analysing datasets by integrating with CKAN to use grids, graphs, maps.

Scholarly workflows #or2017

Abstracts

Supporting Tools in Institutional Repositories as Part of the Research Data Lifecycle by Malcolm Wolski, Joanna Richardson

Have been working on research data management in context of the whole research data lifecycle. Started asking question: once research data management is under control, what will be the next focus? Their answer was research tools. Produced two journal articles:

  • Wolski, M., Howard, L., & Richardson, J. (2017). The importance of tools in the data lifecycle. Digital Library Perspectives, 33(3), in press
  • Wolski, M., Howard, L., & Richardson, J. (2017). A trust framework for online research data services. Publications, 5(2), article 14 https://doi.org/10.3390/publications5020014

Research life cycle: Data creation and deposit (plan and design, collect and capture) -> Managing active data (Collect and capture, collaborate and analyse) -> Data repositories and archives (manage, store, preserve; share and publish) -> Data catalogues and registries

Research data repositories vary a lot. Collection or ecosystem? Open or closed? End point or part of workflow? Why is it hard to build them? Push-and-pull between re-usability and preservation:

  • technical aspects
  • interoperability
  • lega/regulatory/ethical constraints
  • one-off activity or continuous
  • diversity of accessibility issues
  • diversity of re-usability issues

The average number of research tools per person was 22 per person (includes Word, ResearchGate, email through to SurveyMonkey, Dropbox, Figshare, through to R and really specialised ones). Kramer and Bosman (2016) divided tools into assessment, outreach, publication, writing, analysis, discovery, preparation phases. Tools exploding as research activity scales up, collaboration increases. Large-capacity projects being funded. Data science courses upskilling researchers.

Researchers use lots of tools as part of the data workflow. The institution may manage data, but have no ownership of workflow. Since data has to move seamlessly between tools, interoperability is key – but how do we built these interoperable workflows and infrastructures?

Need to remember repository is only part of the research ecosystem. Need to take an institutional approach – or approaches rather than a single design solution. Look at main workflows and tools used – check out research communities who may already have the solutions – focus must be meeting the researchers’ needs.

Q: Will we see researchers use fewer tools as disciplinary workflows develop?A: Probably not but will see more integration between them eg Qualtrics adding an R connector.

Research Offices As Vital Factors In The Implementation Of Research Data Management Strategies by Reingis Hauck

Have a full-text repository on DSpace, building data repository on CKAN. What if we build something (at great expense) and they don’t come? We need cultural change. Eg UK seems far ahead but only 16% of respondents are accessing university RDM support services in 2016.

They have data repository, and provide support service by research office, library and IT services.

Research offices provides support in grant writing; advocates on policies; helps with internal research funding; report to senior leadership. Their toolkit:

  • need to win research managers over – explain how important it is
  • embedded an RDM-expert
  • upskilled research office staff about data management planning and how to make a case for data management.

Look out for game changers:

  • eg large collaborative research projects – produce lots of data and need to share it to be successful so more likely to listen
  • DMP preview as standard procedure for proposal review and training on proposal writing. (Want data management planning to be like brushing your teeth: you do it every day and if you forget you can’t sleep.)
  • adapt incentives – eg internal funding for early career researchers requires data management plans
  • use existing networks – researchers go to lots of boards and meetings already so feed this as a topic like any other topic
  • engage with members of DFG[German science foundation] review board – to get them to draw up criteria to reward researchers doing it

Cultural change towards open science can be supported by your research office. Let’s team up more!

Towards Researcher Participation in Research Information Management Systems by Dong Joon Lee, Besiki Stvilia, Shuheng Wu

RIMS – include ResearchGate, Academia, Google Scholar; ORCID, ImpactStory; PURE, Elements

ResearchGate sends out a flood of emails – good for some, a put-off for others. How can we improve our RIMS to improve researcher engagement?

Interviewed 15 researchers then expanded to survey 412 participants; also analysed metadata on 126 ResearchGate profiles of participants. Preliminary findings:

  • Variety of different researcher activities in RIMS eg write manuscripts, interact with peers, curate, evaluate, look for jobs, monitor literature, identify¬† collaborators, disseminate research, find relevant literature.
  • Different levels of participation: readers may have a profile but don’t maintain it or interact with people; record managers maintain their profile, but don’t interact with others; community members maintain profiles but also interact with others etc.
  • Different motivations to maintain profile: to share scholarship (most popular); improve status, enjoyment, support evaluation, quality of recommendations, external pressure (least popular)
  • Different use of metadata categories: people tend to use the person, publication, and research subject catories. Maybe research experience, but rarely education, award, teaching experience, other other.
    • In Person most people put in first, last name, affiliation, dept;
    • Publication: Most use most of these except only 30% of readers share the file – about 80% of record managers and community member

Want to develop design recommendations to enable RIMS to increase participation.